2026-09-19T16:05:49Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/81864 2023-07-11 col_2142_5131 col_2142_10761 com_2142_5130 com_2142_10755 com_2142_234

Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs U of I Only Embargo set by: Seth Robbins for item 83145 Lift date: Forever Reason: Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs Roth, Dan Small, Kevin 2015-09-25T20:20:44Z 2015-09-25T20:20:44Z 10000-01-01 2009 2009 Secondly, we introduce the interactive feature space construction protocol, which uses a more sophisticated interaction to incrementally add application-targeted domain knowledge to the feature space. Whereas active learning restricts the interaction to additional labeled data, the interactive feature space construction protocol better utilizes the domain expert by focusing direct modification of the feature space to improve performance and reduce sample complexity. Through this protocol, we demonstrate further improvements on our entity/relation extraction system. Made available in DSpace on 2015-09-25T20:20:44Z (GMT). No. of bitstreams: 2 license.txt: 4848 bytes, checksum: 96035ab3f5e1c23cc7138a224ce498bd (MD5) 3392477.pdf: 2576407 bytes, checksum: 6ce78e202a9c282590d46e411c5660e7 (MD5) Previous issue date: 2009 129 p. Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2009. http://hdl.handle.net/2142/81864 (MiAaPQ)AAI3392477 eng Artificial Intelligence Interactive Learning Protocols for Natural Language Applications text Computer Science Computer Science University of Illinois at Urbana-Champaign Dissertation Ph.D.